Transformation of the Investment Structure of Industry and its Impact on Technological Development

The relevance of the study stems from the persistent gap between the growth of investment in new technologies in Russian industry and the absence of a proportionate increase in the share of innovative products. This calls for a tool that can quickly identify at which stage of the investment–technology cycle the return is lost. The aim of the work is to propose a methodology for rapid diagnostics of gaps in the investment–technology cycle. To this end, the following tasks are addressed: building a conceptual closed-loop model comprising the stages of investment, absorption, linking, innovation output, and feedback; developing the Transformation Closure Coefficient (TCC); and identifying typical gaps based on a review of publications from 2020–2025. The scientific novelty lies in combining disparate concepts into a single operational framework that makes it possible to identify bottlenecks without complex calculations. The practical significance is the possibility of rapid self-diagnosis for enterprises and industry regulators. Main results . A TCC is proposed, calculated as the ratio of the growth rate of technological intensity to the growth rate of investment in new technologies, i.e. as an elasticity adjusted by the geometric mean of three conditions: absorptive capacity, interorganizational network density, and digital maturity. The geometric mean penalises weak links but, unlike the minimum, allows partial compensation and is less sensitive to measurement error; the minimum is retained as a conservative variant for early warning. The literature review made it possible to systematize typical gaps for each stage of the cycle. The TCC is positioned as a screening tool: it does not establish causal relationships and is not intended for cross-industry comparisons, but only points to the weak link. The ranking of objects is noted to be robust to the method of aggregating barriers. A conclusion is drawn about the possibility of moving from general calls to targeted work with specific barriers.

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Published
2026-10-29
DOI
https://doi.org/10.67931/1998-5533-2026-3-102-108
Primary Topic
Economic and Technological Developments in Russia
Type
article
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article

Transformation of the Investment Structure of Industry and its Impact on Technological Development

D. I. Lokotnikov
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Economic and Technological Developments in Russia
article

Transformation of the Investment Structure of Industry and its Impact on Technological Development

D. I. Lokotnikov
article en

Abstract

The relevance of the study stems from the persistent gap between the growth of investment in new technologies in Russian industry and the absence of a proportionate increase in the share of innovative products. This calls for a tool that can quickly identify at which stage of the investment–technology cycle the return is lost. The aim of the work is to propose a methodology for rapid diagnostics of gaps in the investment–technology cycle. To this end, the following tasks are addressed: building a conceptual closed-loop model comprising the stages of investment, absorption, linking, innovation output, and feedback; developing the Transformation Closure Coefficient (TCC); and identifying typical gaps based on a review of publications from 2020–2025. The scientific novelty lies in combining disparate concepts into a single operational framework that makes it possible to identify bottlenecks without complex calculations. The practical significance is the possibility of rapid self-diagnosis for enterprises and industry regulators. Main results . A TCC is proposed, calculated as the ratio of the growth rate of technological intensity to the growth rate of investment in new technologies, i.e. as an elasticity adjusted by the geometric mean of three conditions: absorptive capacity, interorganizational network density, and digital maturity. The geometric mean penalises weak links but, unlike the minimum, allows partial compensation and is less sensitive to measurement error; the minimum is retained as a conservative variant for early warning. The literature review made it possible to systematize typical gaps for each stage of the cycle. The TCC is positioned as a screening tool: it does not establish causal relationships and is not intended for cross-industry comparisons, but only points to the weak link. The ranking of objects is noted to be robust to the method of aggregating barriers. A conclusion is drawn about the possibility of moving from general calls to targeted work with specific barriers.

(3)
Peter the Great St. Petersburg Polytechnic University (RU)
Industry, innovation and infrastructure
Openalex Percentile: Top 6%
Economic and Technological Developments in Russia
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